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Muscle Activity, Mechanical Work and Efficiency at Ventilatory Threshold During Maximal and Sub-Maximal Treadmill Exercise

2004· article· en· W4232870764 on OpenAlexaff
Olivier Serresse, Greg J. Mulligan, Maggie Nuziale

Bibliographic record

VenueMedicine & Science in Sports & Exercise · 2004
Typearticle
Languageen
FieldMedicine
TopicCardiovascular and exercise physiology
Canadian institutionsLaurentian University
Fundersnot available
KeywordsVentilatory thresholdTreadmillBicepsElectromyographyMedicineVO2 maxWorkloadCardiologyPhysical therapyIntensity (physics)Physical medicine and rehabilitationInternal medicineHeart ratePhysics

Abstract

fetched live from OpenAlex

0192 PURPOSE: To examine the effects of maximal and sub maximal steady-state treadmill exercise on muscle recruitment and activation, their relationships with the mechanical work and efficiency. METHODS: A group of thirteen non-endurance trained male subjects were exposed to an incremental maximal treadmill test during which oxygen consumption and electromyography (EMG) were collected. Fortyeight hours following the maximal test, two 10-minute constant workload treadmill exercise at intensities of 20% above (supra-VT) and below (sub-VT) the ventilatory threshold (VT) determined during the VO2max test. During these two tests the oxygen consumption and the EMG were monitored. A digital video camera was used to capture individual motions during the max and the sub-max on treadmill. The subjects were also asked to run on a 10 meters platform passing through a force plate at the supra-VT and sub-VT speeds. The 4 sub maximal tests were randomly assigned and separated by at least 15 minutes of passive rest. RESULTS: The iEMGexercise intensity relationships showed a strong and significant correlation for each muscle monitored suggesting a linear relationship; r = 0.75, 0.86, 0.83 for the vastus lateralis (VL), biceps femoris (BF), and gastrocnemius lateralis (GL) respectively. Based on the subsequent findings of paired t-tests this relationship was found to have a threshold during the incremental test. Further this iEMG threshold was correlated (r = 0.81) to the ventilatory threshold (VT) as determined from metabolic parameters. A significant iEMG threshold was also noted in the VL during the supra-VT workload. The muscle activity during the incremental test was significantly greater than the muscle activity from the same muscle during the sub maximal workloads when matched for VO2, workload and respiratory exchange ratio (RER). The mechanical efficiency decreased as the intensity increased during the max test and the two sub max tests. CONCLUSIONS: The inability of the current study to determine the specific mechanism of the EMG thresholds despite the correlation with the VT, suggests that no conclusion can be made regarding the relationship that may exist between these 2 parameters. Although not clearly depicted in the current results, the activation of agonist muscles within each functional group of muscles of the lower limb is the likely mechanism of the discrepancies in muscle activation between the incremental and the constant workload exercises.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.012
GPT teacher head0.251
Teacher spread0.238 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2004
Admission routes1
Has abstractyes

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